Scenario Based Modeling for Very Large Scale Simulations

K. Zia, A. Ferscha, A. Riener, M. Wirz, D. Roggen, Kamil Kloch, P. Lukowicz
{"title":"Scenario Based Modeling for Very Large Scale Simulations","authors":"K. Zia, A. Ferscha, A. Riener, M. Wirz, D. Roggen, Kamil Kloch, P. Lukowicz","doi":"10.1109/DS-RT.2010.20","DOIUrl":null,"url":null,"abstract":"In order to develop complexity science based modeling, prediction and simulation methods for large scale socio-technical systems in an Ambient Intelligence (AmI) based smart environment, we propose a scenario based modeling approach. With a case study on AmI technology to support the evacuation from emergency scenarios, i.e. the Life Belt, a wearable computing systems for vibro-tactile directional guidance, we introduce the concept of model scaling from a micro to a macro level. Aligned with the scenario, we present how crowd simulation strategies encoded into a small scale simulation setup can be extended to a mixed-level simulation based on combining model aspects also coming from the large scale model. The experimental results of a real evacuation trail at a local railway station are incorporated to compare the evacuation efficiency for three strategies: (i) Potential Map, (ii) Evacuees familiarity of the exits and (iii) Exits usage optimization. A comparison with the earlier results from small scale simulation suggest that a real large scale simulation results may not be similar to that of small scale simulation due to dynamics of crowd built up and complexity of building structure.","PeriodicalId":275623,"journal":{"name":"2010 IEEE/ACM 14th International Symposium on Distributed Simulation and Real Time Applications","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE/ACM 14th International Symposium on Distributed Simulation and Real Time Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DS-RT.2010.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

In order to develop complexity science based modeling, prediction and simulation methods for large scale socio-technical systems in an Ambient Intelligence (AmI) based smart environment, we propose a scenario based modeling approach. With a case study on AmI technology to support the evacuation from emergency scenarios, i.e. the Life Belt, a wearable computing systems for vibro-tactile directional guidance, we introduce the concept of model scaling from a micro to a macro level. Aligned with the scenario, we present how crowd simulation strategies encoded into a small scale simulation setup can be extended to a mixed-level simulation based on combining model aspects also coming from the large scale model. The experimental results of a real evacuation trail at a local railway station are incorporated to compare the evacuation efficiency for three strategies: (i) Potential Map, (ii) Evacuees familiarity of the exits and (iii) Exits usage optimization. A comparison with the earlier results from small scale simulation suggest that a real large scale simulation results may not be similar to that of small scale simulation due to dynamics of crowd built up and complexity of building structure.
基于场景的超大规模模拟建模
为了在基于环境智能(AmI)的智能环境中发展基于复杂性科学的大规模社会技术系统建模、预测和仿真方法,我们提出了一种基于场景的建模方法。以AmI技术支持紧急情况下的疏散为例,即用于振动触觉定向引导的可穿戴计算系统Life Belt,我们引入了从微观到宏观的模型缩放概念。根据该场景,我们展示了如何将人群模拟策略编码到小规模模拟设置中,并将其扩展到混合级模拟,该模拟基于来自大规模模型的组合模型方面。结合当地火车站真实疏散路径的实验结果,比较了三种策略的疏散效率:(i)潜在地图,(ii)疏散人员对出口的熟悉程度和(iii)出口使用优化。通过与前期小尺度模拟结果的比较表明,由于所建人群的动态性和建筑结构的复杂性,实际的大尺度模拟结果可能与小尺度模拟结果不太相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信